Larger male Yellow Warbler ( Setophaga petechia ) occupy smaller home ranges over winter in natural and agricultural sites in western Mexico
Bibliographic record
Abstract
Agroecosystems are becoming increasingly important bird habitats as natural Neotropical habitats are converted to agriculture at a rate of 3.5 million ha annually. We still know little about how some of the most common herbaceous crops (e.g., maize, sorghum) are used by wintering birds and the consequences of wintering in these agroecosystems. We used radio-tracking to estimate home ranges of 49 wintering Yellow Warblers (<em>Setophaga petechia</em>) across agriculture and two natural habitats of known quality for Yellow Warblers (high-quality riparian forest and poor-quality coastal vegetation) in Mexico. We assessed whether traits related to competitiveness (sex, age, body size, and migratory origin) interacted with land cover to influence home range size and if home range size influenced annual (apparent) return probability. We found that home range size of wintering Yellow Warblers is highly variable (range = 0.02–3.99 ha) and influenced by land cover, sex, and body size. Home ranges in high-quality riparian forest were smaller than those in coastal vegetation and agriculture. Across all land covers, males tended to have smaller home ranges than females (males: mean = 0.56 ha, 84% CI = 0.36–0.77 ha, females: mean = 0.90 ha, 84% = 0.65–1.16 ha). Body size did not influence home range size for females, but larger males had smaller, presumably better-quality territories than smaller males. In agricultural sites, this meant larger birds (predominantly males) had small, exclusive territories in the hedgerow, while smaller males and females had large, non-exclusive home ranges in the crops. Our work shows that the different components of low-intensity agriculture provide foraging opportunities for different population segments. Because agriculture intensification is expected to increase in Latin America, retaining hedgerows, small field sizes, and crop heterogenicity is important to ensure co-benefits for people and birds.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".